Interstitial lung diseases (ILD) lead to around 1 in 100 deaths in the UK. Some people’s condition gets worse (also known as progression) despite treatment. Predicting whose disease will progress is difficult.
Healthcare professionals use breathing tests to monitor ILD progression. However, these tests are limited as they are:
Influenced by how much effort a patient is capable of during an assessment
Difficult to perform
Vary on a day-to-day basis
When healthcare professionals suspect that someone has ILD, they perform a high-resolution computed tomography (HRCT) scan. HRCT scans produce detailed images of the lungs. These scans are usually used to monitor ILD over time, with radiologists interpreting the images. However, there is potential for HRCT scans to be used in other ways.
Artificial intelligence (AI) can be used to analyse HRCT scans to track disease progression over time. This is known as quantitative CT or qCT.
Project aims
We want to explore whether the qCT approach could highlight which patients are more likely to get worse. It might also pick up disease progression earlier than traditional methods. This will hopefully allow a more personalised approach to treating ILD.
As part of the project we will investigate whether single-photon emission computed tomography (SPECT) could help guide decisions about ILD treatment.
SPECT is a type of HRCT scan where the patient is injected with a small amount of a radioactive tracer to highlight specific processes in the body. After this a special camera creates 3D images of the tracer inside the body.
What we hope to achieve
We hope to provide evidence supporting the use of qCT in clinical practice and identify new ways of providing a more accurate prognosis for patients.